Machine Learning for Stress Detection: A LightGBM-Based Approach Using Bayesian Optimization
AIUB Journal of Science and Engineering (AJSE) · 2026
Abstract e pubblicazione originale
L’abstract è consultabile nella fonte originale. Non viene ripubblicato qui perché non risulta verificata una licenza compatibile.
Leggi nella fonte originale ↗Parole chiave
Emotion and Mood RecognitionArtificial Intelligence in HealthcareContext-Aware Activity Recognition Systemsstress detectionstress predictionLightGBMBayesian optimizationhyperparameter optimizationwearable sensorsInternet of Thingsenvironmental characteristicstemperaturehumiditystep countnon-invasive physiological monitoringdata loss prevention
Come citare questo studio
Mohammad Rabib Uddin, Md. Saniat Rahman Zishan, Shameem Ahmad, Upama Dev. (2026). Machine Learning for Stress Detection: A LightGBM-Based Approach Using Bayesian Optimization. AIUB Journal of Science and Engineering (AJSE). DOI: 10.53799/s67m2287
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